A data engineer monitoring pipelines across three screens, with a server room glowing behind the glass

Service

Data Engineering & Integration

If two teams pull the same report and get different numbers, the problem is usually not the dashboard. It is the systems feeding it. We build and repair the plumbing that collects, cleans and combines your data, so every report starts from the same trusted source.

Book a discovery call

You should be able to ask where a number came from and get an answer the same day.

A pipeline operations dashboard: nightly load throughput by hour, source freshness against target, failure reasons and a run log

What we build

Everything between your source systems and the reports your teams rely on. Built properly, tested, and documented so your own people can maintain it.

Getting data out of your systems

We connect to your CRM, finance system, product database and anything else that matters, on a schedule or in real time. If someone changes a field at the source, the process stops and tells us, instead of quietly feeding you wrong numbers for a month.

Turning raw data into usable tables

Raw system data is rarely in a shape anyone can report on. We build the logic that cleans it, joins it and shapes it into tables your analysts can actually use, organised so a new person can find their way around it.

Making it run on time, every time

Everything runs in the right order, on the right schedule. If something fails overnight, the system retries, then alerts a named person, and there is a written procedure for putting it right.

Catching bad data before your board does

We add automatic checks: no duplicate customers, no missing dates, no sudden unexplained drop in yesterday's sales. The checks run every time the data does, and anything reported externally gets the strictest ones.

Being able to trace any number back

For any figure in any report, you can see exactly which tables and which systems it came from. It is generated from the code itself, so it stays accurate as things change.

Keeping it fast and affordable

As data grows, rebuilding everything each night gets slow and expensive. We change the heaviest parts to process only what is new, which usually cuts both the runtime and the bill significantly.

Built to be handed over

We build it so your team can run it without us. That shapes every decision from day one, rather than being something we worry about at the end. Nothing is stored on our laptops, nothing depends on a consultant remembering how it works, and there is no lock-in.

All the code and infrastructure sits in your accounts from day one
Written instructions for the problems we actually hit while building it
Hands-on sessions with your engineers, not a handover document nobody reads

How the work runs

Find out what you actually have

We look at what is really being queried, not just what the documentation says. This is where we discover the spreadsheet feeding a board report that nobody mentioned.
Fix one report end to end

We take a single report and rebuild everything beneath it, then check the new numbers match the old ones before going any further.
Repeat, faster each time

The second report reuses much of the first one's foundations, so each one after that takes noticeably less time.
Hand the keys over

Your team makes a change and ships it while we watch and advise, rather than the other way round.

What changes

You hear about problems first

Not from a customer, and not in a board meeting. The costly mistakes are the ones nobody notices for weeks, and these checks are designed to catch exactly those.

Every number has an answer

When someone asks where a figure came from, you can show them in minutes instead of starting an investigation.

Changes stop taking weeks

Adding a new field or a new report becomes a routine job for your team, rather than a project that needs three people to coordinate.

An engineer working beside server racks in a data centre

Your team ends up owning this

We build it so your people can run it, change it and extend it without calling us. That is the point of the engagement, not an afterthought at the end of it.

Common questions

Do we need to replace our data warehouse first?

Usually not. Most of the improvement comes from the logic and the testing, which work on whatever platform you already have. If we think a platform change is genuinely needed, we will tell you, and we would move you across gradually rather than all at once.

Can you work with what we have already built?

Yes, and that is the more common request. We normally start by adding checks to what exists, because those checks tend to reveal the real problem faster than rebuilding from scratch would.

What do you need from us?

System access, and about an hour with someone who knows the business rules. The most valuable checks are the ones only your people can describe, things like 'an order should never have a delivery date before its order date'.

Also part of this work

The approved scope from the existing site, which the first draft narrowed too far.

Warehouse and lakehouse design

Deciding the shape of where your data lands, not just how it gets there. Structured, semi-structured and unstructured data each need different handling.

Streaming, where it is genuinely needed

Kafka or Spark when the business needs data in seconds rather than overnight. We will say when a nightly batch would do the same job for far less.

On-premises, cloud and hybrid

Connecting systems across all three, including the ones that cannot move and still have to take part.

Airflow, dbt and Azure Data Factory

We work in whichever of these you already have, rather than introducing a fourth.

Sensor and IoT data

Bringing machine data together with business systems, which is what makes predicting failures possible.

Ready to turn complexity into your next advantage?

Tell us which report you do not trust, and we will tell you what it would take to fix it.